Eng Experimentation (after midterm)

Voltmeter

measures voltage across an element

Ammeter

measures current through a circuit element

Digital Oscilloscope (DSO)

Samples input voltage, converts it to a digital format & stores it in memory

Multiplexers (MUX)

an electronic selector switch, used as a “traffic controller” in a system with multiple sensors

Analog-to-Digital (A/D) Converters

required to convert analog transducer signal into digital code used by the computer

An N-bit A/D converter provides how many values?

2^N possible values

Increment of A/D convertors =

(upper limit - lower limit)/# of possible values

Sources of error in A/D conversion

resolution & associated quantization error, saturation error, conversion error

Parameter Design

What are we looking for? Define objectives, identify variables

Extraneous Variables

Variables that cannot be controlled but will affect the value of the measured values

Measurement Design

What & How? Equipment & technique selection, measurement plan

Analysis Design

What to do with the data?

Discrete Sampling

non-continuous tracks, records data at discrete times, leads to misinterpretation of data

Sampling Rate Theorem

The sample rate must be greater than 2x the highest frequency of the original signal

Random Variable

a variable whose possible values are outcomes of a random phenomenon

Sample Space

set of all possible outcomes of an experiment

Probability

Likelihood of occurrence of an event

Population

the entire collection under consideration

Sample

a subset of the population being studied

Distribution Function

a graphical relationship used to represent the values of a random variable

Normal Probability Distribution Function

used to describe variation in physical properties that are continuous, variations due to random error

Central Limit Theorem

If n is sufficiently large, the x values follow a normal distribution

Student t-distribution

used if sample sizes are small & population standard deviation is unknown

Three-Sigma Test

exclude data outside the range of 3 standard deviations from the mean

Residuals

Difference between measured value & line of best fit

Experimental Uncertainty Analysis

The process of identifying & quantifying errors/uncertainties

5 Categories of Elemental Error

calibration uncertainties, data-acquisition uncertainties, data-reduction uncertainties, uncertainties due to methods, other uncertainties

Data-Acquisition Uncertainties

random variation of measurand, installation effects, conversion uncertainties

Data-reduction Uncertainties

caused by a variety of errors & approximations

Uncertainties due to methods

assumptions in calculations, uncertainties’ due to lack of repeatability & hysteresis

Truncation Error

introduced from rounding of result values